The use of ChatGPT and other large language models in surgical science

potential benefits of RPD, its role in the treatment of pancreatic head cancer remains uncertain. There is a need for well-designed studies to compare the efficacy and safety of RPD versus conventional open PD This grant proposal seeks to address this gap in knowledge by conducting a randomized controlled trial (RCT) or observational study to evaluate the role of RPD in patients with pancreatic head cancer. The study aims to investigate the primary and secondary outcomes associated with RPD and open PD, including length of hospital stay, complication rates, mortality, and survival. The results of this study will provide valuable information on the benefits and risks of RPD compared to conventional open PD and have significant implications for the treatment of patients with pancreatic head cancer. .

applied to clinical notes, such as surgical reports, if LLMs are integrated into an electronic health record environment.
In theory, if LLMs were integrated into clinical environments, they could be used to extract information from electronic health records or other data repositories. This would automate data collection for research purposes and potentially mitigate the challenges associated with manual extraction, such as time consumption and human error. For example, a researcher might prompt the system to extract surgical outcome measures from a surgical report. Additionally, LLMs could be used to answer clinician queries directly by analysing the available patient data and providing a comprehensive answer. This could promote more efficient patient management, such as when a clinician needs a summary of a patient's therapy proceedings.
To consider the potential of LLMs in clinical decision-making, it is important to recognize the significance of language models like PubMed GPT and BioGPT, which are trained on medical knowledge 4,5 . In a mature setting, LLMs could be utilized in clinical workflows, where they automatically evaluate patient information and produce a patient management plan that surgeons can use as a reference point or consider in their decision-making process. This has the potential to streamline the decision-making process, increase efficiency, and ensure that patients receive optimal care.
Although LLMs have the potential to be highly beneficial, there are several important considerations to keep in mind. For example, in terms of text generation and improvement, it is crucial for surgical scientists to understand the limitations of current LLMs. One of the most significant issues is known as 'neural hallucinations,' where the model generates text that is factually incorrect or nonsensical, despite appearing confident in its ability 6 . For instance, an LLM might suggest using churros, a type of fried pastry, as surgical instruments due to their size and flexibility 7 . Additionally, because LLMs are trained on specific datasets, there is a risk of introducing biases into the model's output. Therefore, it is essential to thoroughly evaluate the output of an LLM before incorporating it into any work. When using these models for writing tasks, surgeon-scientists should be aware of these limitations and carefully check the validity of the model's output.
To ensure the reliability and safety of LLMs, it is important to consider the potential issues that may arise when using them for theoretical applications. For example, when using LLMs for research data extraction, it is possible that the model may provide incorrect or biased conclusions, leading to low-quality data. Similarly, when LLMs are employed in patient management, it is necessary to approach their application with caution due to the ethical and legal implications. In the event that clinicians base their decisions on information provided by an LLM, it is unclear who bears the responsibility if something goes wrong. Therefore, once LLMs are implemented in clinical settings, it is critical to establish clear guidelines and rules for their use.
In conclusion, language models like ChatGPT have numerous potential applications in surgical science, ranging from text generation and improvement to data extraction and clinical decision-making. The use of these models can support surgeon-scientists in various areas, including writing, data collection, and even patient management. However, it is important to keep in mind that language models are not flawless and should be used in these areas with caution. As the Recap of the study design, infrastructure, budget, and timeline Statement of the study team's commitment to conducting the study in accordance with ethical and regulatory standards.

Prompt by us:
Now write part I, the introduction 4. Response by ChatGPT: Pancreatic cancer is a highly aggressive disease with a poor prognosis, and it remains one of the most challenging cancers to treat. In the United States, pancreatic cancer is the fourth leading cause of cancer-related deaths, and the ve-year survival rate for pancreatic cancer is only 10%. Surgical resection remains the only potentially curative treatment for pancreatic cancer, and the Whipple procedure or pancreaticoduodenectomy (PD) is the most common surgical approach for tumors located in the pancreatic head. However, PD is a complex and invasive surgery associated with a high risk of complications, including bleeding, infection, and pancreatic stula. As a result, there has been a growing interest in developing minimally invasive surgical approaches for PD, including robotic pancreatoduodenectomy (RPD).
RPD is a novel surgical technique that uses robotic-assisted instruments to perform PD with improved precision and visualization, potentially reducing the risk of complications and facilitating quicker recovery times. However, despite the potential bene ts of RPD, its role in the treatment of pancreatic  Fig. 1 Example of the use of ChatGPT for surgical science field continues to advance, it will be essential to monitor developments and assess the impact of language models on the surgical science field. Ultimately, with responsible and thoughtful implementation, these models have the potential to be a valuable tool in surgical science and clinical care by augmenting, not replacing, human expertise.